Travel Times around Renaissamce Festival

Classes ‘tbl_df’, ‘tbl’ and 'data.frame':   138 obs. of  13 variables:
 $ tmc            : chr  "118P15109" "118P15110" "118P15111" "118N15109" ...
 $ country        : chr  "USA" "USA" "USA" "USA" ...
 $ state          : chr  "Minnesota" "Minnesota" "Minnesota" "Minnesota" ...
 $ county         : chr  "Scott" "Scott" "Scott" "Scott" ...
 $ distance       : num  1.402 0.838 0.676 1.112 0.528 ...
 $ road_number    : chr  "CR-18" "CR-18" "CR-18" "CR-18" ...
 $ road_name      : chr  NA NA NA NA ...
 $ latitude       : num  44.8 44.8 44.8 44.8 44.8 ...
 $ longitude      : num  -93.4 -93.4 -93.4 -93.4 -93.4 ...
 $ direction      : chr  "Northbound" "Northbound" "Northbound" "Southbound" ...
 $ sequence       : num  1 2 3 3 2 1 24 25 26 27 ...
 $ free_flow_tt   : num  99 99 50 112 13 20 3 116 257 130 ...
 $ free_flow_speed: num  51 30.5 48.7 35.7 146.2 ...
NULL

We combine all of the downloaded trip data for the area from the TTRMS.exe tool.

 [1] "CR-42_Eastbound_118N15512_to_118N15511.csv"  
 [2] "CR-42_Westbound_118P05284_to_118P05285.csv"  
 [3] "MN-13_Northbound_118P05351_to_118P05352.csv" 
 [4] "MN-41_Northbound_118P05380_to_118P05381.csv" 
 [5] "MN-41_Southbound_118N05381_to_118N05380.csv" 
 [6] "US-169_Northbound_118P05065_to_118P05066.csv"
 [7] "US-169_Northbound_118P05069_to_118P05070.csv"
 [8] "US-169_Northbound_118P05070_to_118P05071.csv"
 [9] "US-169_Southbound_118N04465_to_118N04464.csv"
[10] "US-169_Southbound_118N05070_to_118N05069.csv"
[11] "US-169_Southbound_118N05071_to_118N05070.csv"
[12] "US-212_Westbound_118N18737_to_118N18736.csv" 

The total dimensions of the combined dataset is 1893888 rows and 15 columns.

head(TMC_data)

Data contains 5 rows with either missing or invalid lat/lon values and will be ignored

Introduction

We will look at each TMC individually.

TMCs in Scott County

Tab 1

US-169_Southbound_118N04465_to_118N04464

Unequal factor levels: coercing to characterbinding character and factor vector, coercing into character vectorbinding character and factor vector, coercing into character vector

Sparkline

We now treat the average travel time per day as a time series. Below is a plot that isolate out the trend and the seasonality of the data set.

Tab 2

CR-42_Westbound_118P05284_to_118P05285

Unequal factor levels: coercing to characterbinding character and factor vector, coercing into character vectorbinding character and factor vector, coercing into character vector

Data contains 2 rows with either missing or invalid lat/lon values and will be ignored

We now treat the average travel time per day as a time series. Below is a plot that isolate out the trend and the seasonality of the data set.

Tab 3

US-169_Northbound_118P05065_to_118P05066

Unequal factor levels: coercing to characterbinding character and factor vector, coercing into character vectorbinding character and factor vector, coercing into character vector

We now treat the average travel time per day as a time series. Below is a plot that isolate out the trend and the seasonality of the data set.

Tab 4

US-169_Southbound_118N05070_to_118N05069

Unequal factor levels: coercing to characterbinding character and factor vector, coercing into character vectorbinding character and factor vector, coercing into character vector

We now treat the average travel time per day as a time series. Below is a plot that isolate out the trend and the seasonality of the data set.

Tab 5

US-169_Southbound_118N05071_to_118N05070

Unequal factor levels: coercing to characterbinding character and factor vector, coercing into character vectorbinding character and factor vector, coercing into character vector

We now treat the average travel time per day as a time series. Below is a plot that isolate out the trend and the seasonality of the data set.

Tab 6

MN-13_Northbound_118P05351_to_118P05352

Unequal factor levels: coercing to characterbinding character and factor vector, coercing into character vectorbinding character and factor vector, coercing into character vector

We now treat the average travel time per day as a time series. Below is a plot that isolate out the trend and the seasonality of the data set.

Tab 7

MN-41_Southbound_118N05381_to_118N05380

Unequal factor levels: coercing to characterbinding character and factor vector, coercing into character vectorbinding character and factor vector, coercing into character vector

Data contains 1 rows with either missing or invalid lat/lon values and will be ignored

We now treat the average travel time per day as a time series. Below is a plot that isolate out the trend and the seasonality of the data set.

Tab 8

MN-41_Northbound_118P05380_to_118P05381

Unequal factor levels: coercing to characterbinding character and factor vector, coercing into character vectorbinding character and factor vector, coercing into character vector

We now treat the average travel time per day as a time series. Below is a plot that isolate out the trend and the seasonality of the data set.